
"""simple docstring"""



import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


a       :						Optional[Any]       		=		['''small''', '''medium''', '''large''']

a       :						int       		=		'''lm_head.decoder.weight'''
a       :						int       		=		'''lm_head.weight'''


def 			_UpperCamelCase						(    _A       ,   _A   )     ->	Optional[int]:





    """simple docstring"""

    _UpperCAmelCase        = torch.load(_A   )
    _UpperCAmelCase        = d.pop(_A   )
    os.makedirs(_A       ,   exist_ok=_A   )
    torch.save(_A       ,   os.path.join(_A       ,   _A   )   )


if __name__ == "__main__":
 a       :						Dict       		=		argparse.ArgumentParser()
 parser.add_argument('''--dialogpt_path''', default='''.''', type=str)
 a       :						Union[str, Any]       		=		parser.parse_args()
 for MODEL in DIALOGPT_MODELS:
  a       :						List[Any]       		=		os.path.join(args.dialogpt_path, F"{MODEL}_ft.pkl")
  a       :						Tuple       		=		F"./DialoGPT-{MODEL}"
  convert_dialogpt_checkpoint(
      checkpoint_path,
      pytorch_dump_folder_path,
  )

"""simple docstring"""



from ....configuration_utils import PretrainedConfig
from ....utils import logging


a       :						Dict       		=		logging.get_logger(__name__)

# TODO: upload to AWS
a       :						Tuple       		=		{
    '''yjernite/retribert-base-uncased''': (
        '''https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json'''
    ),
}




class 		a_    (			_UpperCAmelCase						):
    a   :					int			     =					'retribert'







    def __init__(      self      :							Optional[Any]  ,       __UpperCamelCase      :							Optional[Any]=3_05_22  ,       __UpperCamelCase      :							int=7_68  ,       __UpperCamelCase      :							Any=8  ,       __UpperCamelCase      :							Dict=12  ,       __UpperCamelCase      :							List[Any]=30_72  ,       __UpperCamelCase      :							List[Any]="gelu"  ,       __UpperCamelCase      :							Optional[int]=0.1  ,       __UpperCamelCase      :							int=0.1  ,       __UpperCamelCase      :							Union[str, Any]=5_12  ,       __UpperCamelCase      :							Dict=2  ,       __UpperCamelCase      :							Tuple=0.0_2  ,       __UpperCamelCase      :							List[str]=1e-12  ,       __UpperCamelCase      :							int=True  ,       __UpperCamelCase      :							str=1_28  ,       __UpperCamelCase      :							Union[str, Any]=0  ,       **__UpperCamelCase      :							Any  ,       )		->List[Any]:






        '''simple docstring'''






        super().__init__(pad_token_id=__UpperCamelCase  ,       **__UpperCamelCase  )

        _UpperCAmelCase        = vocab_size
        _UpperCAmelCase        = hidden_size
        _UpperCAmelCase        = num_hidden_layers
        _UpperCAmelCase        = num_attention_heads
        _UpperCAmelCase        = hidden_act
        _UpperCAmelCase        = intermediate_size
        _UpperCAmelCase        = hidden_dropout_prob
        _UpperCAmelCase        = attention_probs_dropout_prob
        _UpperCAmelCase        = max_position_embeddings
        _UpperCAmelCase        = type_vocab_size
        _UpperCAmelCase        = initializer_range
        _UpperCAmelCase        = layer_norm_eps
        _UpperCAmelCase        = share_encoders
        _UpperCAmelCase        = projection_dim